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1. Terminology
The statistical analysis functionality includes the following modules, providing users with detailed and user-friendly analytical capabilities.
| Name | Description |
|---|---|
| Data Dashboard | The data dashboard is the core of the statistical analysis functionality, providing an intuitive interface for users to quickly understand key performance metrics of mini programs. Through the dashboard, users can view real-time data, historical trends, user behavior analysis, and more. The dashboard typically includes charts, digital dashboards, and key metric cards that visualize data to help users make data-driven decisions. |
| Page Data | The page data statistics module focuses on tracking and analyzing user behavior across different pages of the mini program. It records key metrics such as page views, time spent, bounce rates, etc., helping developers understand which pages are most popular, how much time users spend on each page, and how frequently users leave pages. This data is crucial for optimizing page layout and improving user experience (this feature is part of the advanced statistics functionality). |
| Performance Data | The performance data statistics module monitors mini program loading times, response speeds, and other performance-related metrics. Through this data, developers can identify performance bottlenecks, optimize code and resources, thereby improving the overall performance and user experience of mini programs (this feature is part of the advanced statistics functionality). |
| Event Statistics | The event statistics module allows developers to track specific events triggered by users within the mini program, such as button clicks, form submissions, etc. By analyzing the frequency of these events and related user behaviors, developers can better understand user needs and preferences, thereby optimizing feature design and increasing user engagement (this feature is part of the advanced statistics functionality). |
| Funnel Analysis | The funnel analysis module focuses on analyzing conversion paths, helping developers understand the user conversion process from entering the mini program to completing specific goals (such as purchases, registrations). By analyzing each stage of the conversion funnel, developers can identify where users drop off and take appropriate measures to improve conversion rates (this feature is part of the advanced statistics functionality). |
| JS Analysis | The JS analysis module focuses on monitoring the execution of JavaScript code in mini programs. It helps developers identify script errors, performance issues, and resource loading problems, thereby optimizing code and improving the stability and response speed of mini programs (this feature is part of the advanced statistics functionality). |
| Real-time Logs | The real-time logs module provides a window for real-time monitoring of mini program operational status. Developers can use this module to view user operation logs, system errors, and other key events to quickly respond to and resolve potential issues. Real-time logs are crucial for quickly locating and fixing problems (this feature is part of the advanced statistics functionality). |
2. Data Dashboard
The data dashboard module provides users with an interface that centrally displays key performance indicators (KPIs). The page shows core data for all mini programs collectively or filtered by specific mini program and time period.
Core data includes:
- Visit Count: Total number of visits to the mini program over a past period;
- Visit Duration (seconds): Average duration of each user visit to the mini program;
- Active Devices: Number of active users over a past period;
- New Devices: Number of new users over a past period;
- User Source (Application): Traffic source data (referrals from different applications);
- User Source (Region): Geographic source (provinces, cities, etc.).
On the data dashboard page, you can also click the tabs at the top to view device data information based on different mini programs.
Device data includes:
- Device Retention: Device retention rate over a past period, which can be statistically analyzed by different time periods (such as 1-day retention, 7-day retention, 30-day retention);
- Cumulative Devices: Total sum of cumulative devices over a past period;
- Operating System: Operating system (iOS, Android, etc.);
- Resolution Type: Screen resolution (mobile phone, tablet, etc.);
- Device Model: Mobile device models running the mini program;
- Mini Program SDK Version: Statistical information on the mini program SDK version;
- Mini Program Base Library Version: Statistical information on the mini program base library version.
Click on the card details in the upper right corner of the statistical analysis data to view detailed information distributed by date.
3. Page Data
Page data is the most important basic concept in mini program daily analysis. The relevant statistical indicators in page data are all based on the "page path" level (Path level). If you need to statistically analyze page access data at the "parameter" level (Query level), you can report the relevant data and use the event statistics function for corresponding statistical processing.
In page data statistics, developers can view page statistical data filtered by different mini programs or by mini program and time, specifically including:
- Entry Page Statistics: During the statistical period, the number of times users enter the mini program and visit the first page, sorted from high to low;
- Stay Page Statistics: During the statistical period, the time users spend in the mini program, sorted from high to low;
- Exit Page Statistics: During the statistical period, the number of times the last page visited by users, sorted from high to low;
- Page Visit Count: During the statistical period, the total number of times all pages are visited, sorted from high to low;
- Average Page Visits per Device: During the statistical period, the average number of pages visited per user, sorted from high to low;
- Exit Rate: During the statistical period, the proportion of users leaving the mini program from a certain page, sorted from high to low.
Click on the card details in the upper right corner of the statistical analysis data to view detailed information distributed by date.
4. Performance Data
Performance data provides officially collected performance metrics, including mini program performance statistical indicators across multiple dimensions such as startup, network, operation, and experience, as well as comprehensive performance evaluation reports.
On the performance data page, developers can view page statistical data filtered by different mini programs or by mini program and time, specifically including:
- Crash Rate: The ratio of the number of crashes during mini program operation to the number of visits;
- Stutter Rate: The ratio of the number of stutters during mini program operation to the number of visits;
- Average Cold Start Loading Time (ms): The average loading time for mini program cold starts from startup to the completion of the first page rendering (in milliseconds);
- Average Hot Start Loading Time (ms): The time required for mini program hot starts from startup to the completion of the first page rendering (in milliseconds);
- Average Page Loading Time: The average loading time for all pages of the mini program.
Click on the card details in the upper right corner of the statistical analysis data to view detailed information distributed by date.
5. Event Statistics
Event analysis refers to query analysis functions such as event-based metric statistics, property grouping, and condition filtering. In the event analysis function, users can reasonably configure tracking events and properties according to product characteristics, unleashing the powerful potential of event analysis to answer various segmentation questions about change trends and dimensional comparisons.
Click the add button in the upper right corner of the page, select events and one or more metrics to analyze from the dropdown boxes. All events can analyze the following metrics:
- Total Count: The number of times the event was triggered within the selected time range.
- Device Count: The number of unique devices that triggered the event within the selected time range.
- Average Count per Device: The average number of times unique devices triggered the event within the selected time range.
After creation, click "View Data" in the table to browse the metrics information organized by day for that analysis.
In addition to the default events provided by FinClip, mini program developers can define their own events in the code and perform further analysis based on them.
Events and Properties (Custom Reporting)
The FinClip mini program statistics function supports users in reporting corresponding events and properties in the mini program according to their actual business needs, to meet more flexible data statistics requirements. An event can consist of one or more properties. We need to enter the "Property ID", "Property Name", and "Property Type" that make up the properties, and then enter the event and configure the event properties.
Please Note
- Event IDs that have already been reported or created cannot be modified, as the event ID serves as a unique identifier in the event system. If the current event ID cannot meet the requirements, it is recommended to create a new event ID for data reporting;
- If the association relationship of properties already associated with custom events is modified, it will only affect the data statistics function of the event in the property filtering of event analysis, so please modify according to your needs;
- Property names are case-sensitive. If a lowercase property already exists, you cannot report an uppercase property (for example, if there is already an abc property in the data, you cannot report property names such as ABC, Abc, etc.). The same property in different events must maintain consistent definitions and types, otherwise, the data will fail validation and not be stored; The property value type will be determined when the data is first reported. If the property value type is changed later, type casting will be performed. If successful, the data will be stored; if unsuccessful, the data will be discarded;
6. Funnel Analysis
The funnel model is mainly used to analyze the conversion and loss at each step of a multi-step process.
The funnel model is mainly used to analyze the conversion and loss at each step of a multi-step process.
In the funnel analysis function, there are some basic concepts that need to be understood first:
- Step: Composed of an elemental event/virtual event plus one or more filtering conditions, representing a key step in a conversion process.
- Time Range: The time range selected on the interface refers to the time range in which the first step of the funnel occurs.
- Window Period: The time limit for users to complete the funnel, meaning that only if users progress from the first step to the last step within this time range will it be considered a successful conversion.